Data Governance Lead

Position Summary

We are seeking a
Data Governance Lead to establish and scale the enterprise data governance framework that powers analytics, AI, and autonomous agents. This role will lead
the design and governance of the organization's data catalog, business
glossary, data lineage, semantic layer, and trusted data products using
platforms such as Atlan, Alation, Microsoft Purview, and related technologies.

The ideal candidate
understands that modern governance extends beyond compliance and documentation.
They will build the metadata, business context, semantic models, and trust
frameworks that enable humans and AI agents to consistently discover, understand,
and use enterprise data at scale.

This role will
partner closely with Data Engineering, Analytics, AI/ML, Enterprise
Architecture, Business Teams, and Product Leaders to create an enterprise
knowledge foundation that supports analytics, generative AI, agentic workflows,
and data-driven decision making.

Key Responsibilities

Enterprise Data
Governance Strategy

• Define and execute the enterprise data governance roadmap.
  
• Establish governance processes, operating models, stewardship
  responsibilities, and accountability frameworks.
  
• Develop standards for data quality, metadata management, lineage,
  classification, and access governance.
  
• Drive adoption of governance practices across business and
  technology teams.
  

Metadata &
Knowledge Management

• Lead implementation and optimization of Atlan, Alation, Purview, or
  similar governance platforms.
  
• Build and maintain enterprise business glossaries, taxonomies, and
  knowledge frameworks.
  
• Establish metadata standards that improve discoverability and trust
  in enterprise data assets.
  
• Create governance processes for capturing business context and
  institutional knowledge.
  

Semantic Layer &
Data Products

• Define enterprise semantic layer strategy across analytics and AI
  platforms.
  
• Partner with domain teams to create governed business metrics and
  standardized definitions.
  
• Establish lifecycle management for data products and certified data
  assets.
  
• Enable consistent business logic across reporting, analytics, AI
  solutions, and self-service platforms.
  

AI & Agent
Readiness

• Establish governance frameworks for AI-ready data assets.
  
• Create structures that enable AI systems and autonomous agents to
  understand business context, metrics, definitions, and relationships.
  
• Define standards for contextual metadata, business rules, semantic
  relationships, and knowledge representation.
  
• Partner with AI and Data Science teams to ensure trusted, governed
  data is available for AI applications.
  
• Develop governance controls for AI-generated insights and
  agent-based decision support systems.
  

Data Quality &
Trust

• Establish enterprise-wide data quality standards, monitoring, and
  remediation processes.
  
• Define critical data elements and associated quality metrics.
  
• Develop trust scores, certification processes, and governance
  workflows for enterprise data assets.
  
• Drive continuous improvement of data reliability and usability.
  

Lineage & Impact
Analysis

• Build end-to-end visibility of data lineage across enterprise
  platforms.
  
• Establish impact analysis processes for changes to critical data
  assets.
  
• Improve transparency into how data moves from source systems through
  analytics and AI applications.
  
• Support compliance, audit, and operational risk management
  requirements.
  

Stakeholder
Leadership

• Partner with business leaders to define ownership and stewardship
  for critical data domains.
  
• Facilitate governance councils and cross-functional data
  communities.
  
• Drive adoption and organizational change management initiatives.
  
• Influence senior leaders on the strategic value of governance,
  semantic layers, and AI-ready data foundations.
  

Requirements

Required
Qualifications

• 8+ years of experience in Data Governance, Metadata Management, Data
  Architecture, Analytics, or related disciplines.
  
• Hands-on experience with Atlan, Alation, Microsoft Purview,
  Collibra, or comparable governance platforms.
  
• Strong understanding of metadata management, business glossaries,
  lineage, cataloging, and data quality frameworks.
  
• Experience building semantic models, business metrics frameworks,
  and governed data products.
  
• Understanding of modern cloud data platforms including Azure,
  Snowflake, Databricks, and Microsoft Fabric.
  
• Experience driving cross-functional governance programs in large
  enterprises.
  
• Strong communication and stakeholder management skills.
  

Preferred
Qualifications

• Experience supporting Generative AI, Agentic AI, Knowledge Graph,
  RAG, or AI governance initiatives.
  
• Knowledge of semantic technologies, ontology design, taxonomy
  management, and knowledge representation.
  
• Experience implementing data mesh or domain-oriented data ownership
  models.
  
• Familiarity with AI observability, model governance, and responsible
  AI principles.
  
• Experience defining context frameworks that improve AI and agent
  understanding of enterprise information.